An Innovative Self-Adaptive Configuration Optimization System in Cloud Computing. - Jing Jiang 002; Jie Lu 001; Guangquan Zhang 001 (DASC, 2011)

Scaling-Up Item-Based Collaborative Filtering Recommendation Algorithm Based on Hadoop. - Jing Jiang 002; Jie Lu 001; Guangquan Zhang 001; Guodong Long (SERVICES, 2011)

Graph Based Feature Augmentation for Short and Sparse Text Classification. - Guodong Long; Jing Jiang 002 (ADMA (1), 2013)

Optimal Cloud Resource Auto-Scaling for Web Applications. - Jing Jiang 002; Jie Lu 001; Guangquan Zhang 001; Guodong Long (CCGRID, 2013)

Optimised auto-scaling for cloud-based web service - Jing Jiang 002 (2015)

Evolutionary lazy learning for Naive Bayes classification. - Yu Bai; Haishuai Wang; Jia Wu 001; Yun Zhang; Jing Jiang 002; Guodong Long (IJCNN, 2016)

Co-clustering enterprise social networks. - Ruiqi Hu; Shirui Pan; Guodong Long; Xingquan Zhu 001; Jing Jiang 002; Chengqi Zhang (IJCNN, 2016)

Graph Ladder Networks for Network Classification. - Ruiqi Hu; Shirui Pan; Jing Jiang 002; Guodong Long (CIKM, 2017)

MGAE: Marginalized Graph Autoencoder for Graph Clustering. - Chun Wang; Shirui Pan; Guodong Long; Xingquan Zhu 001; Jing Jiang 002 (CIKM, 2017)

DiSAN: Directional Self-Attention Network for RNN/CNN-Free Language Understanding. - Tao Shen 001; Tianyi Zhou 001; Guodong Long; Jing Jiang 002; Shirui Pan; Chengqi Zhang (AAAI, 2018)

Bi-Directional Block Self-Attention for Fast and Memory-Efficient Sequence Modeling. - Tao Shen 001; Tianyi Zhou 001; Guodong Long; Jing Jiang 002; Chengqi Zhang (ICLR (Poster), 2018)

Adversarially Regularized Graph Autoencoder for Graph Embedding. - Shirui Pan; Ruiqi Hu; Guodong Long; Jing Jiang 002; Lina Yao 001; Chengqi Zhang (IJCAI, 2018)

Reinforced Self-Attention Network: a Hybrid of Hard and Soft Attention for Sequence Modeling. - Tao Shen 001; Tianyi Zhou 001; Guodong Long; Jing Jiang 002; Sen Wang 001; Chengqi Zhang (IJCAI, 2018)

Cross-Domain Deep Learning Approach For Multiple Financial Market Prediction. - Xinxin Jiang; Shirui Pan; Jing Jiang 002; Guodong Long (IJCNN, 2018)

Cost-sensitive Hybrid Neural Networks for Heterogeneous and Imbalanced Data. - Xinxin Jiang; Shirui Pan; Guodong Long; Jiang Chang; Jing Jiang 002; Chengqi Zhang (IJCNN, 2018)

Adversarially Regularized Graph Autoencoder. - Shirui Pan; Ruiqi Hu; Guodong Long; Jing Jiang 002; Lina Yao 001; Chengqi Zhang (CoRR, 2018)

Fast Directional Self-Attention Mechanism. - Tao Shen 001; Tianyi Zhou 001; Guodong Long; Jing Jiang 002; Chengqi Zhang (CoRR, 2018)

Detecting Suicidal Ideation with Data Protection in Online Communities. - Shaoxiong Ji; Guodong Long; Shirui Pan; Tianqing Zhu; Jing Jiang 002; Sen Wang 001 (DASFAA (3), 2019)

Temporal Self-Attention Network for Medical Concept Embedding. - Xueping Peng; Guodong Long; Tao Shen 001; Sen Wang 001; Jing Jiang 002; Michael Blumenstein (ICDM, 2019)

Prototype Propagation Networks (PPN) for Weakly-supervised Few-shot Learning on Category Graph. - Lu Liu 019; Tianyi Zhou 001; Guodong Long; Jing Jiang 002; Lina Yao 001; Chengqi Zhang (IJCAI, 2019)

Attributed Graph Clustering: A Deep Attentional Embedding Approach. - Chun Wang; Shirui Pan; Ruiqi Hu; Guodong Long; Jing Jiang 002; Chengqi Zhang (IJCAI, 2019)

Graph WaveNet for Deep Spatial-Temporal Graph Modeling. - Zonghan Wu; Shirui Pan; Guodong Long; Jing Jiang 002; Chengqi Zhang (IJCAI, 2019)

DAGCN: Dual Attention Graph Convolutional Networks. - Fengwen Chen; Shirui Pan; Jing Jiang 002; Huan Huo; Guodong Long (IJCNN, 2019)

Learning Private Neural Language Modeling with Attentive Aggregation. - Shaoxiong Ji; Shirui Pan; Guodong Long; Xue Li 001; Jing Jiang 002; Zi Huang (IJCNN, 2019)

Attentive Dual Embedding for Understanding Medical Concepts in Electronic Health Records. - Xueping Peng; Guodong Long; Shirui Pan; Jing Jiang 002; Zhendong Niu (IJCNN, 2019)

Feature-Dependent Graph Convolutional Autoencoders with Adversarial Training Methods. - Di Wu 050; Ruiqi Hu; Yu Zheng 013; Jing Jiang 002; Nabin Sharma; Michael Blumenstein (IJCNN, 2019)

Tensorized Self-Attention: Efficiently Modeling Pairwise and Global Dependencies Together. - Tao Shen 001; Tianyi Zhou 001; Guodong Long; Jing Jiang 002; Chengqi Zhang (NAACL-HLT (1), 2019)

Learning to Propagate for Graph Meta-Learning. - Lu Liu 019; Tianyi Zhou 001; Guodong Long; Jing Jiang 002; Chengqi Zhang (NeurIPS, 2019)

Decentralized Learning with Average Difference Aggregation for Proactive Online Social Care. - Shaoxiong Ji; Guodong Long; Shirui Pan; Tianqing Zhu; Jing Jiang 002; Sen Wang 001; Xue Li 001 (CoRR, 2019)

Effective Search of Logical Forms for Weakly Supervised Knowledge-Based Question Answering. - Tao Shen 001; Xiubo Geng; Tao Qin 001; Guodong Long; Jing Jiang 002; Daxin Jiang (CoRR, 2019)

Cost-Sensitive Parallel Learning Framework for Insurance Intelligence Operation. - Xinxin Jiang; Shirui Pan; Guodong Long; Fei Xiong; Jing Jiang 002; Chengqi Zhang (IEEE Trans. Ind. Electron., 2019)

Going Deep: Graph Convolutional Ladder-Shape Networks. - Ruiqi Hu; Shirui Pan; Guodong Long; Qinghua Lu 001; Liming Zhu 001; Jing Jiang 002 (AAAI, 2020)

Self-Attention Enhanced Selective Gate with Entity-Aware Embedding for Distantly Supervised Relation Extraction. - Yang Li 154; Guodong Long; Tao Shen 001; Tianyi Zhou 001; Lina Yao 001; Huan Huo; Jing Jiang 002 (AAAI, 2020)

Attribute Propagation Network for Graph Zero-Shot Learning. - Lu Liu 019; Tianyi Zhou 001; Guodong Long; Jing Jiang 002; Chengqi Zhang (AAAI, 2020)

Competitive and Cooperative Heterogeneous Deep Reinforcement Learning. - Han Zheng; Jing Jiang 002; Pengfei Wei 001; Guodong Long; Chengqi Zhang (AAMAS, 2020)

RatE: Relation-Adaptive Translating Embedding for Knowledge Graph Completion. - Hao Huang; Guodong Long; Tao Shen 001; Jing Jiang 002; Chengqi Zhang (COLING, 2020)

Improving Long-Tail Relation Extraction with Collaborating Relation-Augmented Attention. - Yang Li 154; Tao Shen 001; Guodong Long; Jing Jiang 002; Tianyi Zhou 001; Chengqi Zhang (COLING, 2020)

BiteNet: Bidirectional Temporal Encoder Network to Predict Medical Outcomes. - Xueping Peng; Guodong Long; Tao Shen 001; Sen Wang 001; Jing Jiang 002; Chengqi Zhang (ICDM, 2020)

Cross-Graph: Robust and Unsupervised Embedding for Attributed Graphs with Corrupted Structure. - Chun Wang; Bo Han 003; Shirui Pan; Jing Jiang 002; Gang Niu 001; Guodong Long (ICDM, 2020)

Effective Search of Logical Forms for Weakly Supervised Knowledge-Based Question Answering. - Tao Shen 001; Xiubo Geng; Guodong Long; Jing Jiang 002; Chengqi Zhang; Daxin Jiang (IJCAI, 2020)

Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks. - Zonghan Wu; Shirui Pan; Guodong Long; Jing Jiang 002; Xiaojun Chang; Chengqi Zhang (KDD, 2020)

MESA: Boost Ensemble Imbalanced Learning with MEta-SAmpler. - Zhining Liu 002; Pengfei Wei 001; Jing Jiang 002; Wei Cao 007; Jiang Bian 002; Yi Chang 001 (NeurIPS, 2020)

Cooperative Heterogeneous Deep Reinforcement Learning. - Han Zheng; Pengfei Wei 001; Jing Jiang 002; Guodong Long; Qinghua Lu 001; Chengqi Zhang (NeurIPS, 2020)

Confusable Learning for Large-Class Few-Shot Classification. - Bingcong Li; Bo Han 003; Zhuowei Wang 003; Jing Jiang 002; Guodong Long (ECML/PKDD (2), 2020)

Self-attention Enhanced Patient Journey Understanding in Healthcare System. - Xueping Peng; Guodong Long; Tao Shen 001; Sen Wang 001; Jing Jiang 002 (ECML/PKDD (3), 2020)

Rethinking 1D-CNN for Time Series Classification: A Stronger Baseline. - Wensi Tang; Guodong Long; Lu Liu 019; Tianyi Zhou 001; Jing Jiang 002; Michael Blumenstein (CoRR, 2020)

Multi-Center Federated Learning. - Ming Xie; Guodong Long; Tao Shen 001; Tianyi Zhou 001; Xianzhi Wang 001; Jing Jiang 002 (CoRR, 2020)

Learning Graph Embedding With Adversarial Training Methods. - Shirui Pan; Ruiqi Hu; Sai-Fu Fung; Guodong Long; Jing Jiang 002; Chengqi Zhang (IEEE Trans. Cybern., 2020)

Decentralized Knowledge Acquisition for Mobile Internet Applications. - Jing Jiang 002; Shaoxiong Ji; Guodong Long (World Wide Web, 2020)

Federated Learning for Open Banking. - Guodong Long; Yue Tan; Jing Jiang 002; Chengqi Zhang (Federated Learning, 2020)

Intention Recognition from Spatio-Temporal Representation of EEG Signals. - Lin Yue; Dongyuan Tian; Jing Jiang 002; Lina Yao 001; Weitong Chen 001; Xiaowei Zhao 004 (ADC, 2021)

A Green Pipeline for Out-of-Domain Public Sentiment Analysis. - Ming Xie; Jing Jiang 002; Tao Shen 001; Yang Wang 002; Leah Gerrard; Allison Clarke (ADMA, 2021)

Generalized Test Suite for Continuous Dynamic Multi-objective Optimization. - Chang Shao; Qi Zhao; Yuhui Shi 001; Jing Jiang 002 (EMO, 2021)

Sequential Diagnosis Prediction with Transformer and Ontological Representation. - Xueping Peng; Guodong Long; Tao Shen 001; Sen Wang 001; Jing Jiang 002 (ICDM, 2021)

A Universal Representation Transformer Layer for Few-Shot Image Classification. - Lu Liu 019; William L. Hamilton; Guodong Long; Jing Jiang 002; Hugo Larochelle (ICLR, 2021)

Isometric Propagation Network for Generalized Zero-shot Learning. - Lu Liu 019; Tianyi Zhou 001; Guodong Long; Jing Jiang 002; Xuanyi Dong; Chengqi Zhang (ICLR, 2021)

CO-PILOT: COllaborative Planning and reInforcement Learning On sub-Task curriculum. - Shuang Ao; Tianyi Zhou 001; Guodong Long; Qinghua Lu 001; Liming Zhu 001; Jing Jiang 002 (NeurIPS, 2021)

FedProto: Federated Prototype Learning over Heterogeneous Devices. - Yue Tan; Guodong Long; Lu Liu 019; Tianyi Zhou 001; Jing Jiang 002 (CoRR, 2021)

Federated Learning for Open Banking. - Guodong Long; Yue Tan; Jing Jiang 002; Chengqi Zhang (CoRR, 2021)

Federated Learning for Privacy-Preserving Open Innovation Future on Digital Health. - Guodong Long; Tao Shen 001; Yue Tan; Leah Gerrard; Allison Clarke; Jing Jiang 002 (CoRR, 2021)

SCORE: Spurious COrrelation REduction for Offline Reinforcement Learning. - Zhihong Deng 002; Zuyue Fu; Lingxiao Wang 003; Zhuoran Yang; Chenjia Bai; Zhaoran Wang 001; Jing Jiang 002 (CoRR, 2021)

IMBENS: Ensemble Class-imbalanced Learning in Python. - Zhining Liu 002; Zhepei Wei; Erxin Yu; Qiang Huang; Kai Guo 003; Boyang Yu; Zhaonian Cai; Hangting Ye; Wei Cao 007; Jiang Bian 002; Pengfei Wei 001; Jing Jiang 002; et al. (CoRR, 2021)

Towards Inter-class and Intra-class Imbalance in Class-imbalanced Learning. - Zhining Liu 002; Pengfei Wei 001; Zhepei Wei; Boyang Yu; Jing Jiang 002; Wei Cao 007; Jiang Bian 002; Yi Chang 001 (CoRR, 2021)

MHieR-encoder: Modelling the high-frequency changes across stocks. - Zhineng Fu; Weijun Xu; Ruiqi Hu; Guodong Long; Jing Jiang 002 (Knowl. Based Syst., 2021)

Episodic memory governs choices: An RNN-based reinforcement learning model for decision-making task. - Xiaohan Zhang; Lu Liu 019; Guodong Long; Jing Jiang 002; Shenquan Liu (Neural Networks, 2021)

FedProto: Federated Prototype Learning across Heterogeneous Clients. - Yue Tan; Guodong Long; Lu Liu 019; Tianyi Zhou 001; Qinghua Lu 001; Jing Jiang 002; Chengqi Zhang (AAAI, 2022)

Predicting Outcomes for Cancer Patients with Transformer-Based Multi-task Learning. - Leah Gerrard; Xueping Peng; Allison Clarke; Clement Schlegel; Jing Jiang 002 (AI, 2022)

Machine Teaching-Based Efficient Labelling for Cross-unit Healthcare Data Modelling. - Yang Wang 002; Xueping Peng; Allison Clarke; Clement Schlegel; Jing Jiang 002 (AI, 2022)

BiES: Adaptive Policy Optimization for Model-Based Offline Reinforcement Learning. - Yijun Yang; Jing Jiang 002; Zhuowei Wang 003; Qiqi Duan; Yuhui Shi 001 (AI, 2022)

An Explanation Module for Deep Neural Networks Facing Multivariate Time Series Classification. - Chao Yang 024; Xianzhi Wang 001; Lina Yao 001; Jing Jiang 002; Guandong Xu (AI, 2022)

Positive Unlabeled Learning by Semi-Supervised Learning. - Zhuowei Wang 003; Jing Jiang 002; Guodong Long (ICIP, 2022)

Omni-Scale CNNs: a simple and effective kernel size configuration for time series classification. - Wensi Tang; Guodong Long; Lu Liu 019; Tianyi Zhou 001; Michael Blumenstein; Jing Jiang 002 (ICLR, 2022)

Pareto Policy Pool for Model-based Offline Reinforcement Learning. - Yijun Yang; Jing Jiang 002; Tianyi Zhou 001; Jie Ma; Yuhui Shi 001 (ICLR, 2022)

EAT-C: Environment-Adversarial sub-Task Curriculum for Efficient Reinforcement Learning. - Shuang Ao; Tianyi Zhou 001; Jing Jiang 002; Guodong Long; Xuan Song 001; Chengqi Zhang (ICML, 2022)

Personalized Federated Learning With a Graph. - Fengwen Chen; Guodong Long; Zonghan Wu; Tianyi Zhou 001; Jing Jiang 002 (IJCAI, 2022)

Hierarchical Relation-Guided Type-Sentence Alignment for Long-Tail Relation Extraction with Distant Supervision. - Yang Li 154; Guodong Long; Tao Shen 001; Jing Jiang 002 (NAACL-HLT (Findings), 2022)

Federated Learning from Pre-Trained Models: A Contrastive Learning Approach. - Yue Tan; Guodong Long; Jie Ma; Lu Liu 019; Tianyi Zhou 001; Jing Jiang 002 (NeurIPS, 2022)

On the Convergence of Clustered Federated Learning. - Jie Ma; Guodong Long; Tianyi Zhou 001; Jing Jiang 002; Chengqi Zhang (CoRR, 2022)

Personalized Federated Learning With Structure. - Fengwen Chen; Guodong Long; Zonghan Wu; Tianyi Zhou 001; Jing Jiang 002 (CoRR, 2022)

FedNoiL: A Simple Two-Level Sampling Method for Federated Learning with Noisy Labels. - Zhuowei Wang 003; Tianyi Zhou 001; Guodong Long; Bo Han 003; Jing Jiang 002 (CoRR, 2022)

Unsupervised Video Domain Adaptation: A Disentanglement Perspective. - Pengfei Wei 001; Lingdong Kong; Xinghua Qu; Xiang Yin 006; Zhiqiang Xu 003; Jing Jiang 002; Zejun Ma (CoRR, 2022)

CCPrompt: Counterfactual Contrastive Prompt-Tuning for Many-Class Classification. - Yang Li 154; Canran Xu; Tao Shen 001; Jing Jiang 002; Guodong Long (CoRR, 2022)

Many-Class Few-Shot Learning on Multi-Granularity Class Hierarchy. - Lu Liu 019; Tianyi Zhou 001; Guodong Long; Jing Jiang 002; Chengqi Zhang (IEEE Trans. Knowl. Data Eng., 2022)

SemiNLL: A Framework of Noisy-Label Learning by Semi-Supervised Learning. - Zhuowei Wang 003; Jing Jiang 002; Bo Han 003; Lei Feng 006; Bo An 001; Gang Niu 001; Guodong Long (Trans. Mach. Learn. Res., 2022)

Extracting Local Reasoning Chains of Deep Neural Networks. - Haiyan Zhao; Tianyi Zhou 001; Guodong Long; Jing Jiang 002; Chengqi Zhang (Trans. Mach. Learn. Res., 2022)

Federated Learning on Non-IID Graphs via Structural Knowledge Sharing. - Yue Tan; Yixin Liu 001; Guodong Long; Jing Jiang 002; Qinghua Lu 001; Chengqi Zhang (AAAI, 2023)

Adaptive Policy Learning for Offline-to-Online Reinforcement Learning. - Han Zheng; Xufang Luo; Pengfei Wei 001; Xuan Song 001; Dongsheng Li 002; Jing Jiang 002 (AAAI, 2023)

Continual Task Allocation in Meta-Policy Network via Sparse Prompting. - Yijun Yang; Tianyi Zhou 001; Jing Jiang 002; Guodong Long; Yuhui Shi 001 (ICML, 2023)

Does Continual Learning Equally Forget All Parameters? - Haiyan Zhao; Tianyi Zhou 001; Guodong Long; Jing Jiang 002; Chengqi Zhang (ICML, 2023)

Prompt Federated Learning for Weather Forecasting: Toward Foundation Models on Meteorological Data. - Shengchao Chen; Guodong Long; Tao Shen 001; Jing Jiang 002 (IJCAI, 2023)

Structured Federated Learning through Clustered Additive Modeling. - Jie Ma; Tianyi Zhou 001; Guodong Long; Jing Jiang 002; Chengqi Zhang (NeurIPS, 2023)

Unsupervised Video Domain Adaptation for Action Recognition: A Disentanglement Perspective. - Pengfei Wei 001; Lingdong Kong; Xinghua Qu; Yi Ren 006; Zhiqiang Xu 003; Jing Jiang 002; Xiang Yin 006 (NeurIPS, 2023)

Voting from Nearest Tasks: Meta-Vote Pruning of Pre-trained Models for Downstream Tasks. - Haiyan Zhao; Tianyi Zhou 001; Guodong Long; Jing Jiang 002; Chengqi Zhang (ECML/PKDD (2), 2023)

Spatial-temporal Prompt Learning for Federated Weather Forecasting. - Shengchao Chen; Guodong Long; Tao Shen 001; Tianyi Zhou 001; Jing Jiang 002 (CoRR, 2023)

Causal Reinforcement Learning: A Survey. - Zhihong Deng 001; Jing Jiang 002; Guodong Long; Chengqi Zhang (CoRR, 2023)

Curriculum Reinforcement Learning via Morphology-Environment Co-Evolution. - Shuang Ao; Tianyi Zhou 001; Guodong Long; Xuan Song 001; Jing Jiang 002 (CoRR, 2023)

Foundation Models for Weather and Climate Data Understanding: A Comprehensive Survey. - Shengchao Chen; Guodong Long; Jing Jiang 002; Dikai Liu; Chengqi Zhang (CoRR, 2023)

Causal Reinforcement Learning: A Survey. - Zhihong Deng; Jing Jiang 002; Guodong Long; Chengqi Zhang (Trans. Mach. Learn. Res., 2023)

Multi-center federated learning: clients clustering for better personalization. - Guodong Long; Ming Xie; Tao Shen 001; Tianyi Zhou 001; Xianzhi Wang 001; Jing Jiang 002 (World Wide Web (WWW), 2023)

Attentional Gated Res2Net for Multivariate Time Series Classification. - Chao Yang 024; Xianzhi Wang 001; Lina Yao 001; Guodong Long; Jing Jiang 002; Guandong Xu (Neural Process. Lett., 2023)

Beyond Low-Pass Filtering: Graph Convolutional Networks With Automatic Filtering. - Zonghan Wu; Shirui Pan; Guodong Long; Jing Jiang 002; Chengqi Zhang (IEEE Trans. Knowl. Data Eng., 2023)

Embodied Multi-Modal Agent trained by an LLM from a Parallel TextWorld. - Yijun Yang; Tianyi Zhou 001; Kanxue Li; Dapeng Tao; Lusong Li; Li Shen 008; Xiaodong He 001; Jing Jiang 002; Yuhui Shi 001 (CVPR, 2024)

CCPrefix: Counterfactual Contrastive Prefix-Tuning for Many-Class Classification. - Yang Li 154; Canran Xu; Guodong Long; Tao Shen 001; Chongyang Tao; Jing Jiang 002 (EACL (1), 2024)

Federated Prompt Learning for Weather Foundation Models on Devices. - Shengchao Chen; Guodong Long; Tao Shen 001; Jing Jiang 002; Chengqi Zhang (IJCAI, 2024)

What Hides behind Unfairness? Exploring Dynamics Fairness in Reinforcement Learning. - Zhihong Deng; Jing Jiang 002; Guodong Long; Chengqi Zhang (IJCAI, 2024)

Personalized Adapter for Large Meteorology Model on Devices: Towards Weather Foundation Models. - Shengchao Chen; Guodong Long; Jing Jiang 002; Chengqi Zhang (NeurIPS, 2024)

Dual-Personalizing Adapter for Federated Foundation Models. - Yiyuan Yang; Guodong Long; Tao Shen 001; Jing Jiang 002; Michael Blumenstein (NeurIPS, 2024)

Multi-Level Additive Modeling for Structured Non-IID Federated Learning. - Shutong Chen; Tianyi Zhou 001; Guodong Long; Jie Ma; Jing Jiang 002; Chengqi Zhang (CoRR, 2024)

Personalized Interpretation on Federated Learning: A Virtual Concepts approach. - Peng Yan 002; Guodong Long; Jing Jiang 002; Michael Blumenstein (CoRR, 2024)

Influence-oriented Personalized Federated Learning. - Yue Tan; Guodong Long; Jing Jiang 002; Chengqi Zhang (CoRR, 2024)

WALL-E: World Alignment by Rule Learning Improves World Model-based LLM Agents. - Siyu Zhou; Tianyi Zhou 001; Yijun Yang; Guodong Long; Deheng Ye; Jing Jiang 002; Chengqi Zhang (CoRR, 2024)

Personalized Item Representations in Federated Multimodal Recommendation. - Zhiwei Li 007; Guodong Long; Jing Jiang 002; Chengqi Zhang (CoRR, 2024)

False Correlation Reduction for Offline Reinforcement Learning. - Zhihong Deng 002; Zuyue Fu; Lingxiao Wang 003; Zhuoran Yang; Chenjia Bai; Tianyi Zhou 001; Zhaoran Wang 001; Jing Jiang 002 (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Federated Foundation Models on Heterogeneous Time Series. - Shengchao Chen; Guodong Long; Jing Jiang 002; Chengqi Zhang (AAAI, 2025)

Personalized Federated Collaborative Filtering: A Variational AutoEncoder Approach. - Zhiwei Li 007; Guodong Long; Tianyi Zhou 001; Jing Jiang 002; Chengqi Zhang (AAAI, 2025)

DPC: Dual-Prompt Collaboration for Tuning Vision-Language Models. - Haoyang Li; Liang Wang; Chao Wang; Jing Jiang 002; Yan Peng; Guodong Long (CVPR, 2025)

A Tutorial of Personalized Federated Recommender Systems: Recent Advances and Future Directions. - Jing Jiang 002; Chunxu Zhang; Honglei Zhang; Zhiwei Li 007; Yidong Li; Bo Yang 002 (WWW (Companion Volume), 2025)

FedMerge: Federated Personalization via Model Merging. - Shutong Chen; Tianyi Zhou 001; Guodong Long; Jing Jiang 002; Chengqi Zhang (CoRR, 2025)

WALL-E 2.0: World Alignment by NeuroSymbolic Learning improves World Model-based LLM Agents. - Siyu Zhou; Tianyi Zhou 001; Yijun Yang; Guodong Long; Deheng Ye; Jing Jiang 002; Chengqi Zhang (CoRR, 2025)

Federated Adapter on Foundation Models: An Out-Of-Distribution Approach. - Yiyuan Yang; Guodong Long; Tianyi Zhou 001; Qinghua Lu 001; Shanshan Ye; Jing Jiang 002 (CoRR, 2025)

Federated Low-Rank Adaptation for Foundation Models: A Survey. - Yiyuan Yang; Guodong Long; Qinghua Lu 001; Liming Zhu 001; Jing Jiang 002; Chengqi Zhang (CoRR, 2025)

Learn to Preserve Personality: Federated Foundation Models in Recommendations. - Zhiwei Li 007; Guodong Long; Chunxu Zhang; Honglei Zhang; Jing Jiang 002; Chengqi Zhang (CoRR, 2025)

Raw Data Matters: Enhancing Prompt Tuning by Internal Augmentation on Vision-Language Models. - Haoyang Li; Liang Wang; Chao Wang; Siyu Zhou; Jing Jiang 002; Yan Peng; Guodong Long (CoRR, 2025)

FeDaL: Federated Dataset Learning for Time Series Foundation Models. - Shengchao Chen; Guodong Long; Jing Jiang 002 (CoRR, 2025)